Weather Effects of Aerosols in the Global Forecast Model

Abstract

The weather effects of aerosol types were investigated using well-posed aerosol climatology through the aerosol sensitivity test of thermodynamic and hydrometeor fields, and the weather forecast performances in July of 2017. The largest aerosol direct radiative forcing (ADRF) in July was due to dust aerosols at the surface and atmosphere, and sulfate at the top of the atmosphere (TOA), respectively. The ADRF of total aerosols had unilateral tendencies in thermodynamic and hydrometeor fields. The contribution of individual aerosols was linearly additive to those of total aerosols in the heat fluxes, heating rates, humidity, and convective precipitation. However, no such linearity existed in temperature, geopotential height, cloud liquid or ice contents, and large-scale precipitation. Dust was the most influential forcing agent in July among five aerosol types due to the largest light-absorption capacity. Such unilateral tendencies of total aerosols and a part of the linearity of individual aerosols were exerted on the weather systems. The verification of medium-range forecasts showed that aerosols alleviated the overestimation of surface shortwave (SW) downward fluxes, the negative biases of temperature and geopotential heights at TOA and surface, and the underestimation in light and moderate precipitation. In contrast, they enhanced warm biases at the mid-atmosphere and underestimation in heavy precipitations, particularly negative biases in the intertropical convergence zone (ITCZ). Weather forecast scores including current aerosol information were improved in geopotential height (GPH) of the northern hemisphere (NH); however, they got worse in the temperature and the upper atmosphere GPH of the southern hemisphere (SH), which was mostly due to black carbon (BC) aerosols in the tropical regions. The missing mechanisms such as aerosol–cloud interactions, better aerosol spectral optical properties including mixing states and aging, and the near-real-time (NRT) based aerosol loading data are worthwhile to be tried in the near future for fixing the intrinsic underestimation of precipitation in ITCZ and surface radiative fluxes in the desert and biomass burning area.